Chang‐E Ren

1.2k total citations · 1 hit paper
35 papers, 946 citations indexed

About

Chang‐E Ren is a scholar working on Computer Networks and Communications, Control and Systems Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Chang‐E Ren has authored 35 papers receiving a total of 946 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Networks and Communications, 25 papers in Control and Systems Engineering and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Chang‐E Ren's work include Distributed Control Multi-Agent Systems (28 papers), Adaptive Control of Nonlinear Systems (20 papers) and Neural Networks Stability and Synchronization (17 papers). Chang‐E Ren is often cited by papers focused on Distributed Control Multi-Agent Systems (28 papers), Adaptive Control of Nonlinear Systems (20 papers) and Neural Networks Stability and Synchronization (17 papers). Chang‐E Ren collaborates with scholars based in China, Macao and United Kingdom. Chang‐E Ren's co-authors include C. L. Philip Chen, Tao Du, Long Chen, Shaocheng Tong, Yongming Li, Zhiping Shi, Shuai Sui, Dengxiu Yu, Yongming Li and Yong Guan and has published in prestigious journals such as IEEE Access, Information Sciences and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Chang‐E Ren

32 papers receiving 940 citations

Hit Papers

Fuzzy Observed-Based Adaptive Consensus Tracking Control ... 2015 2026 2018 2022 2015 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chang‐E Ren China 16 712 666 151 80 78 35 946
Maobin Lu China 18 525 0.7× 530 0.8× 88 0.6× 53 0.7× 55 0.7× 60 842
Yanhui Zhang China 10 774 1.1× 867 1.3× 248 1.6× 105 1.3× 78 1.0× 21 1.1k
Xiu You China 22 1.2k 1.7× 1.0k 1.5× 155 1.0× 130 1.6× 60 0.8× 37 1.5k
Xinghu Wang China 19 987 1.4× 677 1.0× 208 1.4× 88 1.1× 71 0.9× 82 1.2k
Mahdi Baradarannia Iran 12 568 0.8× 480 0.7× 80 0.5× 62 0.8× 63 0.8× 55 781
Yi Dong China 18 762 1.1× 526 0.8× 82 0.5× 62 0.8× 31 0.4× 66 889
Ziyang Meng Sweden 14 903 1.3× 439 0.7× 68 0.5× 95 1.2× 43 0.6× 26 1.1k
Yang‐Yang Qian United States 13 683 1.0× 585 0.9× 129 0.9× 170 2.1× 66 0.8× 31 912

Countries citing papers authored by Chang‐E Ren

Since Specialization
Citations

This map shows the geographic impact of Chang‐E Ren's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chang‐E Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang‐E Ren more than expected).

Fields of papers citing papers by Chang‐E Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang‐E Ren. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chang‐E Ren. The network helps show where Chang‐E Ren may publish in the future.

Co-authorship network of co-authors of Chang‐E Ren

This figure shows the co-authorship network connecting the top 25 collaborators of Chang‐E Ren. A scholar is included among the top collaborators of Chang‐E Ren based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chang‐E Ren. Chang‐E Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Nan, Chang‐E Ren, & Siyao Cheng. (2025). Privacy-preserving and Byzantine-robust federated broad learning with chain-loop structure. Neurocomputing. 636. 129975–129975.
2.
Ren, Chang‐E, et al.. (2025). FBL-HA: A hybrid aggregation scheme for heterogeneous federated broad learning. Computer Networks. 274. 111810–111810.
3.
Ren, Chang‐E, et al.. (2024). Event-triggered-based encoding–decoding consensus control of continuous-time multi-agent systems under DoS attacks. Journal of the Franklin Institute. 361(7). 106761–106761. 3 indexed citations
4.
Ren, Chang‐E, et al.. (2024). Adaptive Impulsive Consensus of Nonlinear Multiagent Systems With Limited Bandwidth Under Uncertain Deception Attacks. IEEE Transactions on Systems Man and Cybernetics Systems. 54(8). 4592–4604. 9 indexed citations
5.
Ren, Chang‐E, et al.. (2023). FBL-ET: A federated broad learning framework based on event trigger. Knowledge-Based Systems. 265. 110366–110366. 4 indexed citations
7.
Ren, Chang‐E, et al.. (2023). Event-triggered $$\textrm{H}_\infty $$ consensus control for input-constrained multi-agent systems via reinforcement learning. Control Theory and Technology. 22(1). 25–38. 2 indexed citations
8.
Li, Junhui, Chang‐E Ren, & C. L. Philip Chen. (2022). Adaptive impulsive security consensus control of uncertain multi‐agent systems with randomly occurring nonlinearities. International Journal of Robust and Nonlinear Control. 32(18). 9849–9868. 5 indexed citations
9.
Ren, Chang‐E, et al.. (2021). Semi-Supervised Domain Adaption Classifier via Broad Learning System. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2743–2748. 1 indexed citations
10.
Ren, Chang‐E. (2021). Adaptive Fuzzy Disturbance Observer-Based Control for Nonlinear Uncertain Systems with General Exogenous Disturbances. International Journal of Fuzzy Systems. 23(5). 1453–1461. 12 indexed citations
11.
Ren, Chang‐E, et al.. (2021). Adaptive Event-Triggered Control for Nonlinear Multi-Agent Systems with State Time Delay and Unknown External Disturbance. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 3095–3100. 3 indexed citations
12.
Ren, Chang‐E, C. L. Philip Chen, Tao Du, & Yong Guan. (2020). Correction to: Fuzzy Adaptive Leader-Following Consensus Control for Nonlinear Multi-Agent Systems with Unknown Control Directions. International Journal of Fuzzy Systems. 22(2). 748–748. 1 indexed citations
13.
Ren, Chang‐E, C. L. Philip Chen, Tao Du, & Yong Guan. (2019). Fuzzy Adaptive Leader-Following Consensus Control for Nonlinear Multi-Agent Systems with Unknown Control Directions. International Journal of Fuzzy Systems. 21(7). 2066–2076. 27 indexed citations
14.
Yu, Dengxiu, C. L. Philip Chen, Chang‐E Ren, & Shuai Sui. (2019). Swarm Control for Self-Organized System With Fixed and Switching Topology. IEEE Transactions on Cybernetics. 50(10). 4481–4494. 64 indexed citations
15.
Chen, C. L. Philip, Chang‐E Ren, & Tao Du. (2015). Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Multiagent Systems With Heterogeneous Nonlinear Dynamics. IEEE Transactions on Fuzzy Systems. 24(4). 906–915. 263 indexed citations breakdown →
16.
Ren, Chang‐E, Long Chen, C. L. Philip Chen, & Tao Du. (2015). Quantized consensus control for second-order multi-agent systems with nonlinear dynamics. Neurocomputing. 175. 529–537. 34 indexed citations
17.
Ren, Chang‐E & C. L. Philip Chen. (2015). Sliding mode leader‐following consensus controllers for second‐order non‐linear multi‐agent systems. IET Control Theory and Applications. 9(10). 1544–1552. 122 indexed citations
18.
Li, Yongming, Chang‐E Ren, & Shaocheng Tong. (2012). Adaptive fuzzy backstepping output feedback control of nonlinear uncertain time-delay systems based on high-gain filters. Nonlinear Dynamics. 69(3). 781–792. 17 indexed citations
19.
Li, Yongming, Chang‐E Ren, & Shaocheng Tong. (2011). Adaptive fuzzy backstepping output feedback control for a class of MIMO time-delay nonlinear systems based on high-gain observer. Nonlinear Dynamics. 67(2). 1175–1191. 46 indexed citations
20.
Ren, Chang‐E, et al.. (2011). Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer. 1130–1135. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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